Survival Analysis in Medical Research

by Qamruz Zaman, and Karl P Pfeiffer.

Abstract: For the last few decades, special attention has been given to the field of survival analysis. Survival analysis techniques play important part in different areas of research. The purpose of this article is not to elaborate its uses in different fields but to describe some of the frequently used concepts of survival analysis in medical research. Nonparametric techniques (Kaplan-Meier method and Logrank test) of survival analyses are more popular due to simplicity as well as the assumption free property. For multivariate analysis, if the proportional hazards assumption is satisfied, Semi parametric Cox proportional hazard model is used to identify risk factors, while in case of non-proportional hazard model, time dependent regression model is applied to data set. Furthermore, hazard functions of commonly used Survival distributions are described. Some of the under rated areas due to lack of software’s are also discussed.

Key Words: Censoring, Cox regression model, Failure time, Kaplan-Meier survival function, Logrank test, Proportional hazards assumption

Authors:
Qamruz Zaman, ayanqamar@gmail.com
Karl P Pfeiffer,

Editor: Ghorai, Jugal K., jugal@csd.uwm.edu

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